Time-frequency analysis aims to construct a density function of time and frequency to reveal the frequency components in signals to be analyzed and the evolution of the frequency of signals with time.The Wigner distri...Time-frequency analysis aims to construct a density function of time and frequency to reveal the frequency components in signals to be analyzed and the evolution of the frequency of signals with time.The Wigner distribution(WD)is one of the most fundamental and widely used methods for analyzing nonstationary signals in the fields of radar,communication,etc.However,the application of the WD is greatly limited by the existence of interference terms.The adaptive diffusion method proposed to remove the interference terms of the WD by Julien Gosme,et al.is to be invalid in the presence of interference terms generated by signals,whose distributions are interwoven together in the time-frequency plane of the WD.We combine the diffusion technique with difference method for removing these interference terms to improve the resolution and readability of the time-frequency representation of the Cohen class for detecting nonstationary signals.展开更多
This paper develops and analyzes a stochastic derivative-free optimization strategy.A key feature is the state-dependent adaptive variance.We prove global convergence in probability with algebraic rate and give the qu...This paper develops and analyzes a stochastic derivative-free optimization strategy.A key feature is the state-dependent adaptive variance.We prove global convergence in probability with algebraic rate and give the quantitative results in numerical examples.A striking fact is that convergence is achieved without explicit information of the gradient and even without comparing different objective function values as in established methods such as the simplex method and simulated annealing.It can otherwise be compared to annealing with state-dependent temperature.展开更多
The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute th...The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.展开更多
基金Supported by Program for New Century Excellent Talents in University
文摘Time-frequency analysis aims to construct a density function of time and frequency to reveal the frequency components in signals to be analyzed and the evolution of the frequency of signals with time.The Wigner distribution(WD)is one of the most fundamental and widely used methods for analyzing nonstationary signals in the fields of radar,communication,etc.However,the application of the WD is greatly limited by the existence of interference terms.The adaptive diffusion method proposed to remove the interference terms of the WD by Julien Gosme,et al.is to be invalid in the presence of interference terms generated by signals,whose distributions are interwoven together in the time-frequency plane of the WD.We combine the diffusion technique with difference method for removing these interference terms to improve the resolution and readability of the time-frequency representation of the Cohen class for detecting nonstationary signals.
基金partially supported by the National Science Foundation through grants DMS-2208504(BE),DMS-1913309(KR),DMS-1937254(KR),and DMS-1913129(YY)support from Dr.Max Rossler,the Walter Haefner Foundation,and the ETH Zurich Foundation.
文摘This paper develops and analyzes a stochastic derivative-free optimization strategy.A key feature is the state-dependent adaptive variance.We prove global convergence in probability with algebraic rate and give the quantitative results in numerical examples.A striking fact is that convergence is achieved without explicit information of the gradient and even without comparing different objective function values as in established methods such as the simplex method and simulated annealing.It can otherwise be compared to annealing with state-dependent temperature.
基金supported by the National Natural Science Foundation of China(61101173)
文摘The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.
